<p>Based on deviation coupling control, which includes a virtual motor, an improved deviation coupling control strategy is proposed in this paper for a multi-motor speed synchronization system, by introducing a synchronization coefficient and a tracking coefficient. Compared to the traditional deviation coupling control, the proposed method achieves better synchronization and tracking performances during the steady state and start-up. By adjusting the synchronization coefficient and tracking coefficient, the proposed deviation coupling control method allows for independent control of system synchronization and tracking performance during steady state and start-up. The computational load of the proposed method is less than the traditional method. This advantage becomes more significant when the number of motors increases. Furthermore, the synchronization and tracking coefficients are optimized using the particle swarm optimization algorithm. Finally, experimental validations are carried out on a three-motor speed synchronization system.</p>

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Improved deviation coupling control for multi-motor speed synchronization with PSO-based parameter optimization

  • Gan Zhang,
  • Pengzhen Zhang,
  • Wei Hua,
  • Ying Fan,
  • Xibin Guo,
  • Xiaohan Xu

摘要

Based on deviation coupling control, which includes a virtual motor, an improved deviation coupling control strategy is proposed in this paper for a multi-motor speed synchronization system, by introducing a synchronization coefficient and a tracking coefficient. Compared to the traditional deviation coupling control, the proposed method achieves better synchronization and tracking performances during the steady state and start-up. By adjusting the synchronization coefficient and tracking coefficient, the proposed deviation coupling control method allows for independent control of system synchronization and tracking performance during steady state and start-up. The computational load of the proposed method is less than the traditional method. This advantage becomes more significant when the number of motors increases. Furthermore, the synchronization and tracking coefficients are optimized using the particle swarm optimization algorithm. Finally, experimental validations are carried out on a three-motor speed synchronization system.